Construction of a machine-learning-based risk management evaluation model for enterprise financial reporting

Qi Xin

doi:10.1117/12.3032790

12 July 2024 Construction of a machine-learning-based risk management evaluation model for enterprise financial reporting

Qi Xin

Author Affiliations +

Proceedings Volume 13185, International Conference on Communication, Information, and Digital Technologies (CIDT2024) ; 1318504 (2024) https://doi.org/10.1117/12.3032790
Event: International Conference on Communication, Information and Digital Technologies, 2024, Wuhan, China

Abstract

In response to the problems of low efficiency and high time delay in current enterprise financial report risk management evaluation, this article constructs an evaluation model based on machine learning technology. The paper obtained corporate financial data from public financial statements, financial databases, etc., conducted data preprocessing and feature extraction, and used information gain techniques to filter financial statement indicators that have a significant impact on corporate financial risk. It also adopted Support Vector Machine (SVM) to build a prediction model, trained the model using historical financial data, optimizing model parameters with algorithms like gradient descent; finally, the model's performance was evaluated. As the corporate data amount exceeds 1TB, the processing time is only 590.8 seconds, suggesting that the model provides accurate corporate financial risk assessments with short response latency.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qi Xin "Construction of a machine-learning-based risk management evaluation model for enterprise financial reporting", Proc. SPIE 13185, International Conference on Communication, Information, and Digital Technologies (CIDT2024) , 1318504 (12 July 2024); https://doi.org/10.1117/12.3032790

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